13 citations · 20 across the 8 of their papers we have counts for
8 papers
Understanding Entropic Regularization in GANs
Daria Reshetova, Yikun Bai, Xiugang Wu +1
Generative Adversarial Networks are a popular method for learning distributions from data by modeling the target distribution as a function of a known distribution. The function, o…
Pointwise Bounds for Distribution Estimation under Communication Constraints
Wei-Ning Chen, Peter Kairouz, Ayfer Özgür
We consider the problem of estimating a -dimensional discrete distribution from its samples observed under a -bit communication constraint. In contrast to most previous resul…
Batched Thompson Sampling
Cem Kalkanli, Ayfer Ozgur
We introduce a novel anytime Batched Thompson sampling policy for multi-armed bandits where the agent observes the rewards of her actions and adjusts her policy only at the end of…
Asymptotic Performance of Thompson Sampling in the Batched Multi-Armed Bandits
Cem Kalkanli, Ayfer Ozgur
We study the asymptotic performance of the Thompson sampling algorithm in the batched multi-armed bandit setting where the time horizon is divided into batches, and the agent i…
Minimax Bounds for Distributed Logistic Regression
Leighton Pate Barnes, Ayfer Ozgur
We consider a distributed logistic regression problem where labeled data pairs for are distributed across multiple machines…
Lower Bounds for Learning Distributions under Communication Constraints via Fisher Information
Leighton Pate Barnes, Yanjun Han, Ayfer Ozgur
We consider the problem of learning high-dimensional, nonparametric and structured (e.g. Gaussian) distributions in distributed networks, where each node in the network observes an…